Wake-up receiver for radio-on-demand wireless LANs
© Tang et al; licensee Springer. 2012
Received: 31 August 2011
Accepted: 9 February 2012
Published: 9 February 2012
Recent investigations show that access points (APs) of wireless local area networks (WLANs) are idle during much of the time and that an AP in its idle state still consumes a large percentage of power. Wake-up receivers can be used to realize radio-on-demand WLANs, activating APs from the sleep mode only in times of active data communications. A wake-up receiver, sharing the antenna (and the same ISM band) with its co-located WLAN module and exploiting RF energy detection, can be implemented at low cost and run with low power consumption. In this article, we evaluate the effect of an imperfect RF band pass filter (BPF), and suggest a new soft decision method to (i) resist adjacent channel interference leaked by BPF, and, (ii) distinguish wake-up signals from WLAN signals. Extensive simulation and testbed experimental results confirm that the proposed scheme, at a moderate cost, has good performance in delivering wake-up signals and controlling false wake-up events caused by WLAN signals.
Keywordsgreen communications radio-on-demand wireless LANs wake-up receivers signal recognition
Recent years have seen fast growth of wireless local area networks (WLANs) market. Shipment of WLAN chipsets approaches 1 billion in 2010 , among which a large percentage is used in access points (APs). APs, with which mobile nodes associate, extend the Internet backbone. They are always powered on, even in the long idle period, in order to serve potential nodes promptly.
With the trend of global warming, green communications are becoming necessary. Currently, the focus is on how to reduce the huge power consumption due to devices such as routers and switches of the Internet backbone  and base stations of cellular networks, where billions of watts are consumed. Although WLAN APs are also a part of the network infrastructure, their power consumption is not taken seriously yet because a single AP merely consumes a few watts . However, there are a large number of APs and all APs in total do consume a huge amount of power. On the other hand, investigations show that some WLAN APs are idle during most of the time . Therefore, it is both necessary and feasible to reduce power consumption of WLAN APs.
The most effective method to reducing power consumption is to put an idle device into sleep. However, a device in sleep is actually separated from the whole network. To make a device in sleep remain connected in the network, either active or passive wake-up schemes are necessary. Schemes suggested for sensor networks, such as CPU driven duty-cycling  and wake-up receivers [6–10], can be extended to reduce power consumption of WLAN APs as well. This, however, is non-trivial since WLANs have quite different traffic pattern and application scenarios from sensor networks.
Some prior works suggested wake-up receivers for mobile nodes. A secondary low-power radio, "MiniBrick", is used for wake-up signaling in . But the media access control (MAC) protocol for MiniBricks is left untouched. A low-power sensor mote (802.15.4), working on the same 2.4 GHz industrial, scientific and medical (ISM) band as WLAN modules, is used to monitor WLAN channels in . Since only energy is detected without ID matching, false wake-up probability is high. This is refined in , where Zigbee devices are used for more detailed signaling between nodes and APs, to achieve ubiquitous connectivity, high energy efficiency and real time handover. As for ID matching, the work in  suggests using a bloom filter to match a group of IDs.
Sleep scheduling of WLAN APs is heavily affected by the traffic pattern. (1) In the micro time scale, duty-cycling of APs is suggested in  for power-efficient multi-hop extension of access networks. Packets can also be aggregated so as to use the burst transmission and high rate of 802.11n , enabling a longer idle period and sleeping time. Practically, only the WLAN module can be put into sleep in the short idle period. (2) In the macro time scale, the whole system of idle APs can be put into sleep to realize green WLANs . A further optimization is to aggregate flows to few APs and put more APs into sleep. But some APs still have to stay awake even in the idle state in order to ensure coverage. Several methods may be used to activate APs from sleep. An AP is composed of WLAN module, LAN module, CPU, memory, hard disk etc. A simple wake-up policy is to keep the LAN module and WLAN module awake while putting other modules into sleep, and exploit the wake-on-LAN  and wake-on-WLAN  functions for wake-up signaling. According to , although an idle LAN module consumes little power, an idle WLAN module still consumes significant power (on the order of 1W) in monitoring the channel. A more energy-efficient method is to put the WLAN module into sleep as well, and use an auxiliary low-power (no more than 1mW) wake-up receiver to trigger the wake-up event instead. Currently little work is done on this topic for WLAN APs.
In our previous work, we suggested using wake-up receivers to realize radio-on-demand (ROD) WLANs in the 2.4 GHz ISM band , aiming at reducing power consumption of APs due to macro time scale idleness. A wake-up ID (WID) is transmitted by on-off keying (OOK). A wake-up receiver extracts the wake-up signal by a radio-frequency (RF) band pass filter (BPF) and recovers the WID by non-coherent envelope detection. Coexistence of wake-up signals and WLAN signals and recognition of wake-up signals from WLAN signals are studied.
In this article, we further evaluate the effect of adjacent channel interference caused by an imperfect RF BPF. Soft decision (SoftDec) instead of hard decision (HardDec) is suggested. Meanwhile, signal recognition capability is retained. The effect of quantization is also studied. We contribute in two-fold compared with :
The method to detecting wake-up signals in  is based on the assumption that a BPF can completely remove out-of-band interference. However, channels used by WLAN devices are no longer orthogonal when an imperfect BPF is used to extract wake-up signals. A new SoftDec method is suggested for detecting wake-up signals, by mitigating adjacent channel interference leaked due to the imperfect BPF.
Signal recognition in  is limited to HardDec. Furthermore, plain SoftDec, based on correlation, has no capability in distinguishing signals. Proper parameters are suggested for the SoftDec to divide signal space and distinguish wake-up signals from WLAN signals.
Extensive simulation and testbed experiments confirm that the proposed scheme has good performance in delivering wake-up signals and controlling false wake-up events caused by WLAN signals, even in the presence of interference.
The rest of this article is organized as follows: Section 2 discusses design issues of wake-up receivers. Section 3 first presents the system model. Then, processing of wake-up signals and control of false wake-up probability are described in detail. Evaluation results are presented and analyzed in Section 4. Finally Section 5 concludes the article and points out future work.
2 Design issues of ROD WLANs
Comparison of sensor networks and ROD WLANs
Micro time scale
Macro time scale
Seldom a concern
2.1 Traffic pattern and wake-up policy
Traffic pattern heavily affects sleep scheduling and the wake-up policy is limited by the boot time of devices. Sensor networks have low duty cycle where packets are generated occasionally. Sensor nodes, using special embedded system, can wake up with a low latency. Therefore, either duty cycling or wake-up receivers can be used. The micro time scale idleness can be effectively exploited and sensor nodes can sleep between two successive transmissions.
As for WLANs, traffic volume varies with time. In the micro time scale, even when an AP is transmitting packets, there may be short idle periods, during which a WLAN module can be temporarily put into sleep. A WLAN AP uses general OS to process data and management frames. Wake-up of the whole system of an AP (including CPU, memory, and hard disk etc. besides the WLAN module) would take a relatively long time, usually on the order of seconds. Hence, it is not feasible to turn off the whole system of an AP to exploit the short idleness. For the same reason, the duty cycling scheme, which will consume significant power in the periodical sleep/wake-up of the whole system, is not proper for WLAN APs. Therefore, active wake-up receivers are used in this design. It only causes initial wake-up latency, which is still endurable. Interested readers may refer to  for other types of wake-up receivers.
We aim at reducing power consumption of WLAN APs due to the macro time scale idleness. In the macro time scale, most APs in offices are idle in the night while many APs at home are idle in the daytime. In the proposed scheme, all idle APs are put into sleep compared with , where some idle APs are kept awake to ensure coverage. Duty cycling control of a WLAN module in the micro time scale  can be exploited in our ROD WLANs as a supplement.
2.2 Sharing antenna and channel
Most previous works use a separate channel (900 MHz ) for wake-up signals, and require an extra antenna besides the one used by data communication module. As a comparison, in the ROD WLANs, a wake-up transceiver shares antenna with the co-located WLAN module to reduce the hardware cost. As a result, the same frequency band is shared by wake-up transceivers and WLAN modules, which brings about the co-existence problem. As for the 2.4 GHz wake-up receiver suggested for sensor networks , because sensor nodes usually are deployed in remote environments and data signals are sent infrequently, the mutual co-channel interference between data signals and wake-up signals is seldom a big concern and is not touched. In contrast, WLAN signals are far overwhelming compared with wake-up signals and their coexistence is a big issue. In this design, wake-up signals are transmitted on the same channel as WLAN signals, using a compatible MAC protocol. This co-existence mechanism is different from the one studied in , where orthogonal channels are used.
2.3 Tradeoff between simplicity (low power) and reliability
A wake-up receiver is kept awake for a long period during which the host AP is in sleep. Therefore, we aim at realizing reliable wake-up signaling between nodes and APs via simple wake-up transceivers, with the following design targets.
The first target, of course, is low power consumption. To this end, a wake-up receiver is made as simple as possible so as to run at an extremely low power. A traditional receiver, adopting the super-heterodyne architecture, consumes much power for the RF oscillator in frequency conversion. A tuned RF with direct RF envelope detection eliminates the need for a local oscillator . In this article, a similar architecture is adopted. (i) OOK and RF envelope detection are used instead of coherent detection; (ii) Error correction is not implemented, and ID matching is based on correlation.
The second target is reliability. Simplicity might degrade system reliability. (i) Co-channel interference. Wake-up signals, under OOK modulation, have OFF periods, which may be regarded as a clear channel by nearby WLAN devices, and interrupted by new transmission of a WLAN signal. (ii) Adjacent channel interference. It is usually difficult to produce narrow-band BPF in the RF band. As a result, the RF BPF is not very sharp at the band edge, and a wake-up signal extracted with such a BPF is susceptible to interference from WLAN signals on adjacent channels. The interference is especially obvious when the wake-up signal is recovered by non-coherent envelope detection. (iii) False wake-up probability. Without error correction, wake-up events may be falsely triggered by WLAN signals. These problems are specific to ROD WLANs.
2.4 Budget of power consumption of wake-up receiver
The ratio of the power consumption of a ROD AP system (power consumption is the denominator of Equation (1) by using a wake-up receiver) to that of a conventional AP (without a wake-up receiver and always powered on) is η = OAP + PwuRcv/PAP · (1 - OAP) + FPP · (1 - OAP). η decides how much the wake-up receiver can reduce the power consumption. Its third term is usually negligibly small and its second item is also very small. As a result, η mainly depends on OAP and equals to 0.0402 when OAP = 0.04, PWuRcv = 1 mW, and PAP = 5 W.
2.5 Brief summary
2.5.1 Design freedom
Compared with sensor networks where nodes run with battery and have a strict power budget, APs in ROD WLANs have stable power supply and the power consumption of a wake-up receiver can be relaxed a little. In ROD WLANs, a wake-up transmitter works occasionally whose power consumption is much less than that of the main system. Then, part of the complexity of a wake-up receiver can be shifted to the wake-up transmitter.
2.5.2 Design challenge
Different from sensor networks where data signals are sent infrequently and interferences seldom occur, WLAN signals are overwhelming in ROD WLANs and cause many interferences, especially when an imperfect RF BPF is used to extract wake-up signals. Therefore, a wake-up transceiver of ROD WLAN should deliver wake-up signals reliably and have a very low false wake-up probability.
In our previous work , we have already studied the signal co-existence problem and also studied how to detect wake-up signals and how to distinguish wake-up signals from WLAN signals with HardDec. Signal coexistence is realized at the wake-up transmitter, while detecting and distinguishing wake-up signals are realized at the wake-up receiver. In this article, the same wake-up transmitter is used. However, at the receiver, we consider the effect of an imperfect RF BPF and suggest SoftDec for detecting wake-up signals and distinguishing wake-up signals from WLAN signals. For the completeness, the system model of wake-up transceiver and the transmission procedure are briefly described.
3 Wake-up transceiver for ROD WLANs
In this section, we present the detailed design of the wake-up transceiver. First, the system model of the ROD WLANs is defined in Section 3.1. Then, transmission and reception of wake-up signal are described in Sections 3.2 and 3.3, respectively. Next, the necessity of and the method to distinguishing wake-up signals from WLAN signals are explained in Section 3.4 and the performance analysis is given in Section 3.5. In the detection and recognition of wake-up signals, adjacent channel interference is taken into account.
3.1 System model
An AP in the idle state, before entering the sleep mode, notifies the sleep event to its associated STAs, and sets up its WuRcv to monitor a predetermined channel. Then, main system of the AP and WuTx are put into sleep, while the LAN module and WuRcv are kept awake, to accept wake-up requests from either the network side (wake-on-LAN)  or the STA (via WuRcv). The latter is the focus of our research.
where ∥ is the concatenation operation. An exception is that when ESSID of the target AP is unknown, a predetermined WID will be sent to activate all APs and this is actually a broadcast WID. WuTx of a STA transmits a proper WID according to its present state. WuRcv of an AP should store all three WIDs so as not to miss any wake-up requests.
3.2 Transmission of wake-up signals
The wake-up procedure starts when a STA wants to access the external network via an AP, which happens to be in the sleep mode.
3.3 Reception of wake-up signals
WuRcv of the AP extracts the wake-up signal with a RF BPF, followed by amplification, envelope detection and WID matching. WID matching is performed only when a signal is recognized as a wake-up signal. If the detected WID matches the assigned one, a wake-up event is triggered to activate the main system of the AP.
3.3.1 BPF and LPF
The bandwidth of a wake-up signal, containing 95% energy, is about 1 MHz. Although the BPF bandwidth at a WuRcv should be set to this value, in this design, it is set to that of a WLAN channel (20 MHz) for the following reasons: (i) total energy of a WLAN channel is monitored for the purpose of carrier sense. (ii) The envelope of WLAN signals is used in signal recognition. A BPF with a narrower bandwidth changes the distribution of WLAN signals envelope and increases the false probability of signal recognition, as is confirmed by initial experiments.
Since the bandwidth of BPF is much greater than that of wake-up signals, much noise survives the BPF filter and is involved in the envelope. The subsequent low pass filter (LPF, bandwidth is set to 5 × symbol rate), used for smoothing envelopes, can remove some of the out-of-band thermal noise. By simulation, we confirmed that with the following conditions, bit rate = 100 kbps, LPF bandwidth = 1MHz, BPF bandwidth = 20MHz, LPF in the non-coherent envelope detection has a SNR gain of 8dB, compared with 13dB in the coherent detection. In other words, non-coherent detection causes 5dB SNR loss compared with coherent detection. In addition, this SNR loss increases with the rate since a larger LPF bandwidth is required at a higher rate.
3.3.2 Effect of an imperfect BPF
Wireless local area network signals can be transmitted in parallel on orthogonal channels (separated by 25MHz or more) without mutual interference. But with an imperfect BPF, WLAN signals on a channel (F c + 25MHz, e.g., CH6) may leak to a neighboring channel (F c , e.g., CH1) where a wake-up receiver is monitoring the channel. An imperfect BPF has two effects. (1) The number of false wake-up events may be increased since WLANs signals on adjacent channels are also received by the wake-up receiver. (2) Frame error rate may be increased. The OFF period of an OOK modulated wake-up signal means 0. But in the presence of interference, leaked energy will increase the signal energy in the OFF period, which leads to higher bit error rate.
3.3.3 WID matching
The received WID is compared with the assigned WID and a wake-up event is triggered if the WID matches. In the subsequent evaluations, we will further show that HardDec is sufficient when there is no interference. But it is difficult to find a fixed β applicable to all scenarios after taking the potential adjacent channel interference into account. In contrast, SoftDec helps to resist adjacent channel interference leaked by an imperfect BPF.
3.4 Signal recognition
3.5 False probability analysis
In this section, we analyze the false probability of signal recognition. Using Equation (7) in signal recognition, it is equivalent to compare against N · α. A false positive event occurs when a WLAN signal is recognized as a wake-up signal, i.e., for a WLAN signal. A false negative event occurs when a wake-up signal is recognized as a WLAN signal, i.e., for a wake-up signal. In the analysis, we assume that a WLAN signal is longer than the preamble of a wake-up signal, which is true for typical data transmissions.
4 Evaluation and analysis
In this section, we first evaluate the effect of an imperfect BPF and the performance of the proposed scheme under different BPF bandwidths by simulation. Then, we also evaluate the proposed scheme with a simple testbed. These days most WLAN devices in 2.4 GHz use 802.11g. It is required in  that the lowest rate (6 Mbps) of OFDM modulation in 802.11g should be supported at RSSI = -82dBm. Therefore, we will check whether the wake-up receiver can satisfy the same requirement. When evaluating false probability of signal recognition, 802.11g ERP-OFDM signals of eight rates are generated and processed by the same wake-up receiver.
Default parameters used in experiments
Bit rate of wake-up signal
Length of preamble
Length of wake-up ID
802.11g ERP-OFDM, 8rates
Distance of adjacent channels
Signal to interference ratio
-91dBm per 20MHz
Bandwidth of RF band pass filter
65 MHz at 10dB attenuation
Number of runs per evaluation
Channel. WLAN signals can be transmitted in parallel on two orthogonal channels (e.g., Fc = CH1 and Fc + 25MHz = CH6 in Figure 5) without mutual interference. Hence, we assume that a wake-up signal is transmitted on the frequency F c and the interfering WLAN signal is transmitted at 54 Mbps on the frequency Fc + 25 MHz.
Signal power. By default, we consider the case where an interfering WLAN signal arrives at the WuRcv with the same RSSI as the wake-up signal. We will also evaluate the effect of different signal to interference ratio (SIR).
BPF. At the WuRcv, the interfering WLAN signal on Fc + 25 MHz is not sufficiently attenuated by the BPF, and the amount of remaining interference depends on the BPF bandwidth. Several BPF filters, whose 10 dB bandwidths are 25, 35, 45, 55, and 65 MHz, are generated to mimic the different degrees of interference due to incomplete attenuation, and their frequency responses are shown in Figure 5. With SIR equaling to 0dB before BPF, the SIR after BPF is 34.6, 16.5, 10.7, 7.4, and 5.4dB, respectively. The last filter, with the bandwidth being 65 MHz, approaches off-the-shelf BPFs.
Noise. In the evaluation, additive white Gaussian noise is assumed and its power is fixed at -91dBm/20MHz, which is often used in network simulators such as QualNet .
4.1 Envelope distribution and ideal SoftDec
4.2 Practical SoftDec
In the above results, Δ = 0 is the best for SoftDec and offers the max SNR gain compared with HardDec. But in order to distinguish wake-up signals from WLAN signals, a non-zero Δ is necessary.
4.3 Signal recognition under SoftDec
Signal recognition is conducted by comparing MCR of the N-bit preamble of a received signal against a suitable threshold α. N = 20 is chosen according to Figure 7. To find a suitable threshold α, the distribution of MCR is investigated. Figure 12 shows CDF(x) = prob(MCR < x) of wake-up signals and CCDF(x) = prob(MCR > x) of WLAN signals. At a given MCR threshold, CDF of wake-up signals is FNP and CCDF of WLAN signals is FPP. In the ideal case, MCR is 0 for a WLAN signal and 1 for a wake-up signal. Because Δ is chosen to ensure a low FER, MCR of wake-up signals is around 1. But MC error rate of WLAN signals is relatively high (on the order of 10-1 at Δ = 1/4). Then, MCR of WLAN signals is much greater than 0. α is set to 0.8 according to Figure 12. FPP and FNP are almost the same with N = 20 and α = 0.8, as shown in Figure 7.
4.4 Effect of SIR
4.5 FER of SoftDec on the testbed
4.6 Review of power budget
In this section, we review the power budget of the proposed wake-up receiver. The wake-up receiver has a simple structure: the RF part consists of a passive RF BPF, an amplifier and an envelope detector; the baseband part consists of an A/D converter, a signal recognition module and a signal detection module. The amplifier and envelope detector of the RF part usually consume much power. But according to the results in the literatures [6–10], power consumption of the whole wake-up receiver (including the amplifier and envelope detector) for sensor networks is typically below 100 μ W. As for the baseband part, 2-bit A/D is sufficient; the signal recognition module merely requires several comparators and a counter, and the signal detection module is only run when a signal is recognized as a wake-up signal. Accordingly, the baseband part can be realized by an ultra-low power micro-controllerb whose maximal power consumption is no more than 0.9mW. This power consumption can be further reduced by using special hardware. Therefore, the conservative power budget of 1 mW, discussed in Section 2.4, can be realized easily.
5 Conclusion and future work
We suggested wake-up transceivers for realizing ROD wireless LANs. As for the three key functions--signal co-existence, signal detection and signal recognition, the first one is already solved in our previous work . The performance of the latter two is much affected by the adjacent channel interference under imperfect BPFs. In this article, we examined the effect of imperfect RF BPF, and suggested SoftDec and optimal parameters for both signal detection and signal recognition. Simulation and experimental results confirm that the proposed method, with a low complexity, works well in the presence of moderate interferences. In the future, we will build the complete system and evaluate power consumption of the wake-up receiver as well as the whole system of an AP.
aSince each WID is transmitted in a single frame, FER has the same meaning as message error rate. bFor example, MSP430, the 16-bit ultra-low power RISC mixed signal microprocessor from TI, consumes 300 μ A@3V at the active mode and 0.6 μ A@3 V at the standby mode.
This work is supported by the Promotion program for Reducing Environmental loaD through ICT innovation (PREDICT) funded by Ministry of Internal Affairs and Communications, Japan.
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